Main Article Content
Preparing preservice STEM teachers who have very limited teaching experience for such a very challenging job needs specific requirements. The purposes of the study were to develop the STEM PCK-based course using experiential learning coupled with worked example instructional principles and then to examine the impacts of the course on preservice STEM teachers’ STEM PCK and teaching self-efficacy. A convergent parallel mixed-methods design was employed in order to achieve comprehensive views of how the STEM PCK-based course impacts preservice STEM teachers. One of graduate courses was specifically developed and then implemented with 25 participating preservice science and mathematics teachers for 15 weeks in the first semester of 2016 at the Faculty of Education, Naresuan University, Thailand. For data collection, the writing test of STEM PCK conceptions and the STEM teaching self-efficacy instrument was developed and used with all participants as a part of quantitative data collection. While documentary analysis technique, the observation form, individual semi-structure interview with, and focus group discussion were also used in the qualitative part. For data analysis, a paired sample t-test was used along with basic descriptive statistics for quantitative data while content analysis technique was also employed for qualitative data. Drawn on both data, it is found that the developed STEMPCK-based course has positive impact on preservice STEM teachers’ STEM PCK and teaching self-efficacy. The qualitative data also reveal that direct and reflective experiences of STEM teaching and learning are very important for preservice teachers in developing their STEM teaching knowledge and confidence as assisting in making sense of STEM teaching experiences. They also recognize and value available supports and guidance along with opportunities for reflection and discussion with others. This study has provided teacher educators and STEM education community with promising and very useful information about ways to equip preservice teachers with educative tools for STEM education.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The owner of the article does not copy or violate any of its copyright. If any copyright infringement occurs or prosecution, in any case, the Editorial Board is not involved in all the rights to the owner of the article to be performed.
Bengtsson, M. (2016). How to plan and perform a qualitative study using content analysis. Nursing Plus Open, 2, 8-14.
Berg, B. L. (2001). Qualitative research, message for the social sciences (4th ed.). Boston: Allyn and Bacon.
Clark, R. C., Nguyen, F., & Sweller, J. (2006). Efficiency in learning: Evidence-based guidelines to manage cognitive load. San Francisco: Pfeiffer.
Creswell, J. W., & Plano Clark, V. L. (2011). Designing and conducting mixed methods research (2nd ed.). London: Sage Publications.
Desouza, S., Boone, W. J., & Yilmaz, O. (2004). A study of science teaching self-efficacy and outcome expectancy beliefs of teachers in Southern India. Science Education, 88(6), 837–854.
Dewey, J. (1938). Experience and education. New York: Macmillan.
Ejiwale, J. (2013). Barriers to successful implementation of STEM education. Journal of Education and Learning, 7(2), 63-74.
Geddis, A. N. (1993). Transforming subject matter knowledge: The role of pedagogical content knowledge in learning to reflect on teaching. International Journal of Science Education, 15, 673-683.
Goldhaber, D. D., & Brewer, D. J. (1998). When should we reward degrees for teachers? Phi Delta Kappan, 80(2), 134-138.
Gonzalez, H. B., & Kuenzi, J. J. (2012). Science, technology, engineering, and mathematics (STEM) education: A primer. Congressional Research Service, Library of Congress.
Graneheim, U. H., & Lundman, B. (2004). Qualitative content analysis in nursing research: concepts, procedures, and measures to achieve trustworthiness. Nurse education today, 24(2), 105–112. https://doi.org/10.1016/j.nedt.2003.10.001
Grossman, P. L. (1990). The making of a teacher: Teacher knowledge and teacher education. New York: Teachers College Press.
Guskey, T. R. (2002). Professional development and teacher change. Teachers and Teaching: Theory and Practice, 8, 381- 391. http://dx.doi.org/10.1080/135406002100000512
Kelley, T. R., & Knowles, J. G. (2016). A conceptual framework for integrated STEM education. International Journal of STEM Education, 3, 1-11. https://doi.org/10.1186/s40594-016-0046-z
Klassen, R. M., Al-Dhafri, S., Hannok, W., & Betts, S. M. (2011). Investigating pre-service teacher motivation across cultures using the Teachers’ Ten Statements Test. Teaching and Teacher Education, 27, 579-588.
Linn, M. C., Bell, P., & Davis, E. A. (2004). Specific design principles: Elaborating the scaffolded knowledge integration framework. In M. C. Linn, E. A. Davis, & P. Bell (Eds.), Internet environments for science education (pp. 315-340). Lawrence Erlbaum Associates.
Loughran, J. J. (2002). Effective reflective practice: In search of meaning in learning about teaching. Journal of Teacher Education, 53, 33-43.
Lumpe, A. T., Haney, J. J., & Czerniak, C. M. (2000). Assessing teachers' beliefs about their science teaching context. Journal of Research in Science Teaching, 37, 275– 292.
Magnusson, S., Krajcik, J., & Borko, H. (1999). Nature, sources, and development of pedagogical content knowledge for science teaching. In J. Gess-Newsome & N. G. 22 Lederman (Eds.), Examining Pedagogical Content Knowledge: The construct and its implications for science education (pp. 95-132). Dordrecht: Kluwer Academic Publishers.
Mishra, P., & Koehler, M.J. (2006). Technological pedagogical content knowledge: A framework for integrating technology in teacher knowledge. Teachers College Record, 108(6), 1017-1054.
Moon, J. A. (2004). A Handbook of Reflective and Experiential Learning: Theory and Practice. London: Routledge Falmer.
Moore, T., Stohlmann, M., Wang, H., Tank, K., Glancy, A., & Roehrig, G. (2014). Implementation and integration of engineering in K-12 STEM education. In S. Purzer, J. Strobel, & M. Cardella (Eds.), Engineering in Pre-College Settings: Synthesizing Research, Policy, and Practices (pp. 35–60). West Lafayette: Purdue University Press.
Morrison, J. (2006). TIES STEM education monograph series, Attributes of STEM education. Baltimore, MD: TIES.
Nadelson, L. S., Seifert, A., Moll, A., & Coats, B. (2012). i-STEM summer institute: An integrated approach to teacher professional development in STEM. Journal of STEM Education: Innovation and Outreach, 13(2), 69-83.
Northfield, J. (1993). A school-based initiative: An opportunity to better understand the practicum. Australian Journal of Teacher Education, 18(2), 40-45. http://dx.doi.org/10.14221/ajte.1993v18n2.7
Palmer, D. (2002). Factors contributing to attitude exchange among preservice elementary teachers. Science Education, 86, 122-138
Renkl, A. (2005). The Worked-Out Examples Principle in Multimedia Learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 229–245). Cambridge University Press.
Renkl, A., & Atkinson, R. (2007). Interactive learning environments: Contemporary issues and trends. An introduction to the special issue. Educational Psychology Review, 19(3), 235-238. https://doi.org/10.1007/s10648-007-9052-5
Rodgers, C. (2002). Defining reflection: Another look at John Dewey and reflective thinking. Teachers College Record, 104(4), 842-866.
Saxton, E., Burns, R., Holveck, S., Kelley, S., Prince, D., Rigelman, N., & Skinner, E. A. (2014). A common measurement system for K-12 STEM education: Adopting an educational evaluation methodology that elevates theoretical foundations and systems thinking. Studies in Educational Evaluation. http://doi.org/10.1016/j.stueduc.2013.11.005
Schwonke, R., Renkl, A., Krieg C., Wittwer, J., Alven, V., & Salden, R. (2009). The worked-example effect: Not an artefact of lousy control conditions. Computers in Human Behavior, 25, 258-266.
Shapiro, S. S., & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3/4), 591-611.
Shulman, L. S. (1986). Those who understand: Knowledge growth in teaching. Educational Researcher, 15(2), 4-14.
Stohlmann, M., Moore, T. J., & Roehrig, G. H. (2012). Considerations for teaching integrated STEM education. Journal of Pre-College Engineering Education Research (J-PEER), 2(1), 28-34.
Tschannen-Moran, M., & Woolfolk Hoy, A. (2001). Teacher Efficacy: Capturing an Elusive Construct. Teaching and Teacher Education, 17, 783-805. http://dx.doi.org/10.1016/S0742-051X(01)00036-1
Tsupros, N., Kohler, R., & Hallinen, J. (2009). STEM education: A project to identify the missing components. Intermediate Unit 1: Center for STEM Education and Leonard Gelfand Center for Service Learning and Outreach, Carnegie Mellon University, Pennsylvania.
Tuovinen, J., & Sweller, J. (1999). A comparison of cognitive load associated with discovery learning and worked examples. Journal of Educational Psychology, 91, 334-341. doi:10.1037/0022-0618.104.22.1684
Winley, G. K., & Wongcuttiwat, J. (2012). The structure of the information technology profession: A comparison among organizational sectors in Thailand. Electronic Journal on Information Systems in Developing Countries, 51(5), 1–30.
Woolfolk, A. E., & Hoy, W. K. (1990). Prospective teachers' sense of efficacy and beliefs about control. Journal of Educational Psychology, 82(1), 81–91. https://doi.org/10.1037/0022-0622.214.171.124